The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

Qian Li; Yong Qin; Ziyang Wang; Zhongxin Zhao; Minghui Zhan; Yu Liu; Zhiguo Li

doi:10.4236/jilsa.2013.54026

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Journal of Intelligent Learning Systems ... > Vol.5 No.4, November 2013

The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method ()

Qian Li, Yong Qin, Ziyang Wang, Zhongxin Zhao, Minghui Zhan, Yu Liu, Zhiguo Li

Beijing Rail Transit Network Management Co. Ltd., Beijing, China..
Commercial Department of the Australian Consulate-General Guangzhou, Guangzhou, China..
The State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China.

DOI: 10.4236/jilsa.2013.54026 PDF HTML 3,952 Downloads 5,589 Views Citations

Abstract

This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.

Keywords

Urban Rail Transit; Neural Network; Sectional Passenger Flow; Prediction Method

Share and Cite:

Q. Li, Y. Qin, Z. Wang, Z. Zhao, M. Zhan, Y. Liu and Z. Li, "The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method," Journal of Intelligent Learning Systems and Applications, Vol. 5 No. 4, 2013, pp. 227-231. doi: 10.4236/jilsa.2013.54026.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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